A hallmark of cancer cells is deregulation of the apoptotic cell death program. One mechanism to deregulate apoptosis is by overexpressing the antiapoptotic members of the Bcl-2 family of proteins, Bcl-2, Bcl-xl, Bcl-w, A1, and Mcl-1. To restore the ability of cells to undergo apoptosis, small molecules have been designed to inhibit these proteins. ABT-263 is a first-in-class Bcl-2 inhibitor with a high affinity for Bcl-2, Bcl-xl, and Bcl-w. It exhibits potent activity as a single agent against several tumor types. However, most solid tumors are resistant to ABT-263 due to high expression of Mcl-1, to which the drug has a low affinity. Mcl-1 is known to be regulated transcriptionally, translationally, and by proteosome-mediated degradation, and microRNA (miRNA) may also play a role.
MiRNAs are small non-coding RNAs that regulate global gene expression by binding to the 3′ UTRs of their target genes and repressing translation. Many of these small RNAs are expressed at abnormal levels in multiple cancer types. Since miRNAs can regulate hundreds of targets, and each gene can be regulated by hundreds of miRNAs, the identification of miRNA targets has been a challenge. Multiple tools are available for identifying miRNA targets. In general, the criteria for miRNA target identification are (i) the presence of a sequence at the 5′ end of miRNA complementary to the 3′UTR of the mRNA, (ii) favorable thermodynamic hybridization between miRNA and mRNA, (iii) conservation of the miRNA target sites across multiple species, (iv) site context that increases site efficacy (such as AU-rich nucleotide composition near the site, proximity to sites for co-expressed miRNAs, proximity to residues pairing to miRNA nucleotides 13-16, positioning within the 3′-UTR at least 15 nt from the stop codon, and positioning away from the center of long UTRs), (v) miRNA expression versus target gene expression data, and (vi) secondary structure of the target that is conducive to miRNA binding. Unfortunately, the current target prediction tools are unreliable, resulting in a large number of false positives and false negatives. Recently, proteomics has also been employed to facilitate the identification of miRNA targets.